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A digital workshop process decision-making method based on decision tree and expert system

An expert system and process decision-making technology, applied in the field of digital workshops, can solve problems such as low reasoning efficiency, achieve the effects of improving reasoning speed, ensuring completeness, and improving sample quality

Active Publication Date: 2021-12-17
SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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  • Abstract
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  • Claims
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Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention provides a digital workshop process decision-making method based on a decision tree and an expert system, using a decision tree algorithm to train and learn for the digital workshop process production data, generate knowledge rules, and then realize daily Process decision-making rules are found in process production data to overcome the bottleneck of expert knowledge acquisition; in the reasoning process, only the newly added fuzzy facts in the fact base are matched with the fuzzy rule antecedents in the fuzzy rule base, which improves the reasoning speed. Try to avoid the problem of low reasoning efficiency when the number of knowledge rules is large

Method used

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  • A digital workshop process decision-making method based on decision tree and expert system
  • A digital workshop process decision-making method based on decision tree and expert system
  • A digital workshop process decision-making method based on decision tree and expert system

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Embodiment

[0055] 1) Binning processing of process production data

[0056] Taking the electrolytic cell as an example, the selected process parameter variables are electrolysis temperature and aluminum level, and the process decision result quantity is the daily aluminum output of the electrolytic cell. Such as figure 2 , image 3 , Figure 4 Shown are the 2015 aluminum level data distribution map, the electrolysis temperature data distribution map; the electrolytic cell daily aluminum volume data distribution map, it can be seen that the data distribution span is small, in order to reduce the complexity of the subsequent fuzzy rules based on decision tree production, and To improve the generalization ability of fuzzy rules, set fewer equal-width binning intervals for electrolysis temperature and aluminum level, here we set 3; There are more equal-width binning intervals with more aluminum content, here is set to 5. The self-defined binning intervals of electrolysis temperature, al...

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Abstract

The invention relates to a digital workshop process decision-making method based on a decision tree and an expert system, which performs binning processing on the process production data to generate intervalized fuzzy process production data; conducts training and learning on the fuzzy process production data based on a decision tree algorithm, Generate fuzzy rules and import them into the fuzzy rule base; the inference engine is based on the real-time parameter data in the process real-time monitoring database, and performs fuzzy reasoning through interaction with the fuzzy rule base to generate process decisions. The invention conducts training and learning on the process production data of the digital workshop, generates knowledge rules, and then realizes the discovery of process decision-making rules from the daily process production data of the digital workshop, and overcomes the bottleneck of obtaining expert experience knowledge; The added fuzzy facts are matched with the antecedents of the fuzzy rules in the fuzzy rule base, which improves the reasoning speed and avoids the problem of low reasoning efficiency when the number of knowledge rules is large.

Description

technical field [0001] The invention relates to the technical field of digital workshops, in particular to a digital workshop process decision-making method based on a decision tree and an expert system. Background technique [0002] The digital workshop is the comprehensive application of digitalization and network technology in the production workshop. It integrates the information of numerical control equipment and process design system, production organization system and other management systems to form an integrated manufacturing system with comprehensive information flow automation. Due to the industrial characteristics of the digital workshop process, such as various product specifications, complex structure, and high technical difficulty, higher requirements are put forward for the efficiency, stability and reliability of the digital workshop process decision-making, and the intelligent decision-making technology has opened up for this requirement. The new approach, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q50/04
CPCG06Q10/0631G06Q50/04Y02P90/30
Inventor 史海波潘福成里鹏于淼段彬胡国良
Owner SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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